Spatiotemporal directional coherence-based scrolling-text detection for frame rate up-conversion

Abstract

This paper proposes a novel scrolling-text detection method that uses spatiotemporal directional coherence for frame rate up-conversion. Spatiotemporal directional coherence is defined as the coherence level of the spatiotemporal gradient distribution in consecutive frames. Existing scrolling-text detection methods usually detect text using the motion vectors of an image or the distributions of gradient components. The number of motion vectors to determine the scrolling-text decreases at the start and end points of the frame boundary. Therefore, they have difficulty accurately detecting the scrolling text from the start or end points of a frame boundary. The distributions of gradient components can be generated by non-scrolling-text components and they cannot consider the temporal information of consecutive frames, so they may erroneously detect non-scrolling-text regions as the scrolling-text. Unlike the previous methods, which are vulnerable to the presence of texture and noise, the core idea of the proposed method is to use the spatiotemporal directional coherence of the gradient components in the consecutive frames to detect the regions with a dominant edge orientation component for generation of the scrolling-text map and use bit codes from the luminance values to analyze the diversity of luminance patterns for refinement process. With these, the proposed method can further improve the detection accuracy compared to the benchmark methods. The experimental results showed that the proposed method enhanced the average F1 score by up to 0.5195 (a 137.69 % improvement) compared to the benchmark methods. The average computation time per pixel of the proposed method was also reduced by up to 16.205 μs (a 70.57 % reduction) compared to the benchmark methods.